Time in modern world is going really fast. Everyday we can observe new inventions in
technologies, mathematics, chemical, physics, etc.With all of it we can go deeper in understanding of live around.
On one hand it makes live easier, on other hand more complex.

We can look on it from point of  constructing and engineering.  Modern tools can help us to produce more
light and strong structures, safe money and time. Like parametric design which typically refer to biotectonics.
We can find different, great solutions how to produce something from world around (nature), especially in macro world.
It is a difficult goal, because when you want to use this kind of data, you should spent lot of time in details and calculations.
This implies considerable amount of knowledge, but finally it could be great result.
Architects and engineers of nowadays can use all power of mathematics in theirs work. For example a geodesic structure
of British Museum in London by Norman Foster + partners. It was a really specific goal how to cover roof space of quiet old building
and develop courtyard inside. Because of the shape of rooftop it was really difficult to use classic methods of hyperboloid structures.
But they solved this problem by deep mathematician calculations, that helped to build completely light and modern form.

Anyway humanity goes straight forward to future and it would not be a place for old expensive, costly on money and materials
ways of building. For it we should genesis new forms and new types of understanding  Architecture.

BIG Little Denmark project, which attempted to map sociological behavior by simplifying it to the data points of monetary consumption

In DeLanda’s review of Deleuze, one of his primary summaries is that oscillating behaviors form the patterns of actualization behind molecular, biological, and socio-technic structures. If accurate, then this base principle could be used to build virtual models of such processes, and to generate new models based on the same patterns of organization.

The behavioral oscillations in molecular and biological applications are clear, and DeLanda includes illustrative examples. The socio-technic applications are less obvious and, though referenced in passing, are left relatively unexplained. If such behavioral patterns in this context could actually be identified and refined, they might offer a much-needed step toward building sociological models and turning the more elusive factors of the built environment into actionable data points.

[BIG's Little Denmark project attempted to simplify the sociological condition of the built environment into a map of the resources and entertainments monetarily consumed. Economic activity is easily recorded, and therefore easily mapped and modeled. Perhaps if other sociological forces could be mapped as accurately, we could start to superimpose these models in a way that could generate verifiable data.]

Though the existence of swarm intelligence and the emergence of complex intelligent systems is supported through research at many scales, certain questions arise when thinking about implementation at the scale of our cities. Does a knowledge of the existence of emergence as a social phenomenon play into our societal structure? If so, who are the actors in implementing this knowledge? How is it implemented? How do we overcome the paradox of implementing strategies which will strengthen the phenomenologics of swarm intelligence within our societal structure while curbing the development of a top-down state where knowledge of the systems overall operations are reserved only for those who are in the know?

There is a veritable line in the sand between the opposing approaches of top-down organization and bottom-up hive intelligence, but either strategy in isolation does not produce tangible results. Effectively, the bottom is too dumb to produce due to the simplicity of its operations relative to scale of the system. The bottom essentially is composed of components which perform, in the Darwinian sense, simple yes/no computations to accumulate local knowledge that is fed into the database of the system. The system, on the other hand, is far too complex for the derivation of universally applicable rules, and its collective conscience too impatient to wait for the bottom to self-organize. Thus, we see an shift in scale not only in terms of the breadth of the collective knowledge, but also in the understanding of time. The growth of the system results in deeper and deeper clustering of information and the intensive organization of form, differing fundamentally to the invention and application of derived form. We can then begin to redefine the notion of formal design or organization to coincide not with the behavior of the system, but to the behavior of the agent of the system and its local interactions.

The methodology of behavioral design is discussed by Kokkugia in ‘Behavioral Matter’, as it relates to swarm urbanism and the shift from the notion of a ‘master plan’ to that of a ‘master-algorithm’ at the urban scale. Through this re-appropriation, we can see the beginnings of a response to the posited question of implementation, and that the fundamental hierarchies of urbanism such as scalar time and intensity of agents acting in the system are platforms for the development of this logic. For the Melbourne Docklands, Kokkugia proposed urban structures by firstly using the self-organizing design agents of the system to reform the matter in the creation of circulatory and infrastructural networks, and by secondly programming urban elements and topologies with embedded behavioral traits. In this experiment, all elements in the system are conceived as agents which conceptualize and form complex environments through behavioral operations.

The embedding of behavioral design methodologies within urbanism offers a step forward in bridging the gap between top-down intervention and the slow-burning power  of the hive mind. It also manifests the ‘editor’ within the agents themselves, based on an extrapolation of their behavior rather than an derivation from the overall composition of the system. As Kevin Kelly identifies in ‘The Bottom is Not Enough’, editors are a means by which to maximize the efficiency of the collective through moderate top-down intervention, while not hindering its operations. Although he is talking about the world of digital publication, the same basic principles apply at the urban scale as they do to omnipresent information systems such as Wikipedia. Though they operate in principal through bottom-up formation, the need for expertise on a particular subject requires a the existence of an ‘expert’ which can provide a clustered wealth of knowledge. Clustering which occurs in Wikipedia can then be identified as an agent-based algorithm which is embedded from the top-down into the system itself, taking cues from the behavior of the source rather than the overall behavior.

Thompson himself identifies that most websites possess more collective wisdom than any given city, but lack the ability to effectively cluster and process the received information in the same way. As the breadth of digital knowledge continues to widen, the process of editing through embedded behavioral algorithms becomes for complex (Kelly imagines in one day to include controlled edits, peer review, verification and authentication certificates to name a few). If the Wikipedia of 2056 will better represent the idea of a complete encyclopedia due to the ever-increasing complexity of its ‘designed’ editing process, perhaps the same level of complexity embedded into our urban environments can similarly streamline our world.

references:

Kokkugia. “Behavioral Matter”. Swarm Intelligence: Architecture of Multi-Agent Systems. Ed. Neil Leach and Roland Snooks.

Kelly, Kevin. “The Bottom is Not Enough”. Swarm Intelligence: Architecture of Multi-Agent Systems. Ed. Neil Leach and Roland Snooks.

Thompson, Steven. Emergence: the connected lives of ants, brains, cities and software. New York: Scribner; 1 edition (Sept. 10 2002)

Thompson, Steven. Only Connect. thegaurdian. 15 October 2001. Accessed 20 November 2013. http://www.theguardian.com/books/2001/oct/15/society

                                           PATTERNS IN NATURE

image link :  http://www.beyondstillness.net/ taken on 05/12/13

In the essay by Manuel De landa is talking about the “GENESIS OF A FORM”. He doesn’t agree with the western philosophy that conceives matter as inert element forms that comes from the outside and not from the inside. There are two important factors that help create a form in nature which are Mathematics and Thermodynamics.

Deleuze differentiates form into two categories the first is the “strata” and the “self-consistent aggregates”. The Strata being the “trees” and self- consistent aggregates being the “rhizomes”. Both of these result in isomorphic actual forms, but the one has to do with the fusion of homogeneous elements while the other explains the unification of heterogeneous elements. De landa is also explaining how a form emerges from organizational structure of biological, molecular as well all the socio economic environments.

Deleuze was hugely influenced by mathematics and physics and use these to understand and decompose the virtual form as well as use it as a tool to help in actualization of the virtual. The example he uses for the real and virtual is the DNA, the DNA of the embryo is virtual because it has a lot of potential and real is the embryo that is created along with the external influences.

The Form that is created in nature can be seen growing in many different yet morphological patterns. These patterns repeat, coexists, vary and transform in various life forms. Digital logics deals with parametric, swarm technology etc and with the help of digital tools we can simplify these patterns and understand them. I would like to study more about the patterns in nature and research about it and how it can help in Form evolution of a project.

This is a link to  a video done by Yann Pineill & Nicolas Lefaucheux showing how mathematics and diagram go hand in hand .

“Mathematics, rightly viewed, possesses not only truth, but supreme beauty — a beauty cold and austere, without the gorgeous trappings of painting or music.” —Bertrand Russell

http://vimeo.com/77330591#

Mug & Donut

Thompson is a “genius”  descriptive and analytical , Biology + Mathematics = on growth and form , in a context where the theory of evolution was overrated and had no mathematical or physical basis, a formal and structural analysis that led to the morphogenesis and put it in the line of scientific and artistic time known to this day.

The most accurate methodology implemented by Thompson breaks the classical processes and includes the ability to describe and analyze the formal patterns of plants and animals within their natural ecosystems , and concluded his remarks with mathematical and physical results . After his work emphasises the unlimited vision we have about mathematics and describes the endless possibilities this demand, geometrical , physical , mechanical , etc. . Everything could be described and had a reason to be measured by mathematical analysis to be performed on any natural phenomenon , like a drop of water produced by rain, their oblique to act on their natural environment geometric qualities. Its more practical to perform these operations analysis method is known as coordinate , could make a graph analysis , and project the results modified and transformed these analyzes to support their views . Their analyzes ended with conclusions which included them spirals or mathematical relationships describing geometric number sequences like Fibonacci processes.

All topological and zoometric analysis performed through thomson coordinate method , was only the beginning of a practice research through the grid deformations and changes in the geometric parameters defining new comparisons between geometric descriptions of the same species : analysis implemented in mammals, insects and bone topologies , etc. . This led him to question the theory of evolution of Darwin and put on the table all these analyzes explaining evolution and transformation processes using mathematical , physical and mechanical methods.

The standardization of parameters never ceases to be a finite, limiting factor at first when we think we have an endless possibilities by means of mathematics, we forget completely the needs of the environment, not just expect that physics and mechanics tell us as relations or as a space; also are the sensations and perceptions Visual, visually alter objects and create new spaces, perhaps ephemeral spaces that mutate and evolve with the information they receive from each new environment in which they were implanted, with these changes in the way we discover the uniqueness of each new environment.

Intro
When a designer makes a machine that can solve problems, the designer gets credit. When a machine like this can find a method of finding a method of solution, the machine is the one who makes the answer. The machine may be more creative than the designer.

The evolutionary Machine
This paper is about machines that can learn about learning about architecture. These are called architecture machines. When an architect and an architecture machine can work together, this can make an evolutionary system. Computers are useful tools, which do everything that a human will command it to do. Why do we need a machine to be able to learn?
Most things that a computer does make things only work faster. If computers worked smarter as well, then things would be more efficient.
Two concerns in machine assisted architectureArchitects can’t handle large scale problems because they are too complex. But architects ignore small problems because they seem unimportant. Because of this, architects rarely get to see homes that they designed. 
To allow architects to be able to see the homes they design, it would be helpful to have machines that can learn. The machine would have to be able to respond to its environment.
 
The learning Machine
 
The 1943 theorem of  M and P states that a robot constructed with regenerative loops of a certain formal character, is capable of deducing any legitimate conclusion from a finite set of premises. Learning is can be done from several failures which can lead to success. Failure needs to be recognized.

To be able to recognize failure and learn, an architecture machine needs 5 things: 1) heuristic mechanism, 2) a rote apparatus, 3) a conditioning device, 4) a reward selector and 5) a forgetting convenience.
1) Heuristic narrows the search, or limits the search for a solution. When a problem is observed, the machine will recognize the problem and make sure it doesn’t do anything related to what it just did. Thus it limits even more possibilities.
2) Rote learning is the storing (remembering) of an event and associating it with a response.
3) Responses which are repeated become habits
4) a reward selector
5) unlearning bad habits is as important as learning. This way the machine won’t make the same mistake twice
The whole body (of the machine) will always be changing
One supercomputer could be connected to all the other architecture machines, allowing the machines and the humans who operate them to be able to 1) acquire large bursts of computing power, 2) to acquire stored information, 3) to communicate with other architects and other architecture machines
 
The Seeing Machine
 
Communication is the discriminatory response of an organism to a stimulus. The machine needs a stimulus – a way to sense or observe things that happen in its environment.
For a machine to look like its designer, 3 properties are needed: an event, an idea, and a representation.
In an architect-machine partnership the most important sense (out of the 5 senses: See, touch, hear, smell, taste) is to see. Computer graphics are used a lot.
Oliver Selfridge ‘s “Pandemonium” machine “saw” things and said what it was
It’s possible to build an architectural seeing machine that observes different models
This research helps to learn by focusing on visual stuff
Machine is more of a mannerist than a student but it reverses the fashionable role of computersFor eyes of an architecture machine, problem is the opposite. Given a form, generate the criteria… learn from the criteria and someday generate new forms.
Computers are usually used to store information, which is used to aid an architect in designing something which is then created and observed. An architecture machine could look at something that is created and observed, gather the information, and create something better and new.

Events can be seen, heard, smelt, felt, extra-sensory or a motor command.  In an architect-machine partnership the most important sense (out of the 5 senses: See, touch, hear, smell, taste) is to see. Computer graphics are used a lot. 

Oliver Selfridge ‘s “Pandemonium” machine “saw” things and said what it was.

It’s possible to build an architectural seeing machine that observes different models, and this research helps to learn by focusing on visual stuff.  
Machine is more of a mannerist than a student but it reverses the fashionable role of computersFor eyes of an architecture machine, problem is the opposite. Given a form, generate the criteria… learn from the criteria and someday generate new forms.
Computers are usually used to store information, which is used to aid an architect in designing something which is then created and observed. An architecture machine could look at something that is created and observed, gather the information, and create something better and new.

a complex network of rhizomes
Image courtesy: Boney K

Book: A Thousand Plateaus: Capitalism and Schizophrenia
Author: Gilles Deleuze and Felix Guattari
Chapter: I- Rhizome

Rhizome: A horizontal, underground plant stem capable of producing the shoot and root systems of a new plant. (source: www.britannica.com)

Rhizome by Deleuze and Guttari is abstracted by relating it with multiple phenomenons. As per the book Rhizome is multiplicity connected to each other in vivid manner along the plane of consistency. A rhizome is something without a beginning or an end, without any sort of hierarchy, non-linear and with multiple entry and exit points. Rhizome is anti-arborescent model. An arborescent model is something which develops around central core or has central nucleus. Hence rhizome has no privileged center and has bigger dimensions than any arborescent model. This rhizome connect in bigger dimension and in multiple ways with different variety of elements to form assemblagesThese assemblages can be categorized into two main types (a) machinic assemblages: which deals with social and material flows (b) collective assemblages : which deals with sign or linguistic flows.

Further Deleuze and Guttari give introduces principles of rhizomes in order to understand its specific characteristics

1) Principle of connectivity: The rhizome can be connected at any point in any manner. It does not require a specific origin. its collective and continuous.

2)Principle of heterogeneity: What is connected can completely be two different things. Any rhizome connects in heterogeneous manner. Further explained through example of wasp and orchid, where male wasp is attracted to orchid as central part looks like female wasp and hence engages itself in transference of pollen from one to other. similarly is the case with viruses, it carries genetic information and travel from host to host. hence wasp and orchid, viruses and its host connect to form a rhizome

3)Principle of multiplicity: Any rhizome can be multiply connected in varied manner to form acentered, asubjective, interwoven network.

4)Principle of asignifying rupture: A rhizome may be broken but will start up its own lines or new lines by interconnecting and multiplying in a heterogeneous manner. Hence a rhizome can never be destroyed. And it is not necessary that broken rhizome follows similar characteristic once connected to other from a ruptured end. For example a line of ant, if one tries to break the queue within few time it will again form new queue and not be necessary it is the same path as earlier, but will try to regenerate itself. Further explained through the concept of deterritorialization- Where newly designed multiplicity is re-coded with different set of functions rather than following what it was originally designed for. For example the computers were initially designed to perform arithmetic calculation but now its used in varied fields. Thus function of computer is deterritorialized and now reterritorialized for multiple function in varied fields. hence here the function of computers act as rhizome.

5) and 6)Principle of cartography and decalcomania: A rhizome is more like a map, one can enter at any point an exit at any point, its never ending multiplicity. A map is never fixed but its constantly changing. Hence rhizome is map of complexities which can never be traced. As it does not have single point of origin which can be traced back, but a complex network with multiple entry and exit points.

Left: Kazimir Severinovich Malevich’s Suprematism,
Right: Hafenstrasse Office and Residential Development by Zaha Hadid | Hamburg | 1989

image courtesy:
left: http://commons.wikimedia.org/wiki/File:Kazimir_Malevich_-_Supremus_58.jpg

Right: http://archilibs.net/2013/04/21/hafenstrasse-office-zaha-hadid/
The book itself behaves as rhizome as any chapter can be read in any manner. It does not follow a specific format. Such model is interactive as well as intriguing. Such phenomenon can also be understood through various architectural movements. For example new movement of deconstructivism in architecture emerged through literary writings of french philosopher jacques derrida who emerged new branch of deconstructivism in literature from constructivist literature. Also Russian constructivist and futurist art movments inspired architects like Zaha Hadid and coop Himmelblau both in their graphics and geometrical forms.

Image: The Matrix Wallaper
Extract from: http://www.dan-dare.org

From the text of Manuel de Landa
Deleuze and The Genesis of Form

The essay we studied is an interpretation of Manuel de Landa (writer and artist) on the writings of the French philosopher Gilles Deleuze about the genesis of form.

According to De Landa, a constant in the history of Western philosophy, conceives matter as an inert element forms that come from the outside and not from the inside leaving aside the capabilities of the same shape and reducing the variability and the richness expression of matter at a gross concept of mass, in which only simple systems are studied in the same.

However, the author emphasizes the contrasting Gilles Deleuze’s work about Spinoza, in which a new possibility is discovered; resources or components involved in the genesis of the form (all elements) are forcefull for the generation of matter itself, defining the states in which matter is created from the inside out (not from outside) as imminent, ruling the collective behavior of the components and resulting in a geometric shape with divergent capabilities.

Likewise, Deleuze coined the term “divergent actualization” of the French philosopher Henri Bergson, distinguishing between “possible” and “real”, translating this to a network of forms or elements that together acquire a physical reality, I mean, an actualization that may differ from your starting point and ending point, depending on the differentiation of the same, creating a variation of different physical samples and always generating a genuine shape.

De Landa simplifies the complex Deleuzian’s thought coming from the Bergson’s theory, as follows: for Deleuze the “Noumena” (An existing world itself free of any human activity) is a part of the autonomous existence of real forms, which exists in synchrony with the virtual forms, making it is clear that the difference is not only diversity but also the difference is that by which the given is given, I mean, everything that happens (virtual and real) and all that appears is correlated with orders of differences: differences of level, temperature, intensity etc.

Therefore, Deleuze emphasizes the role of virtual singularities can only be captured during the genesis of form, before the final form one is updated and before the difference appears.

To clarify the above, the author points out the latest work of Deleuze, in which mention two very important types of structures “strata” and “self-consistent aggregates”, him refers to the strata as emergent elements through joining homogenous elements, while self-consistent aggregates emerging from the joint of heterogeneous elements. In both processes it is shown divergent actualizations of both the real and virtual form.

To end and completely clarify this text, I would like to define in a more austere way the above concepts. There are virtual diagrams that are possible through realities in the genesis of form. I mean, real processes such as the formation of a rock through layers or strata tends to settle through a “virtual” process to reach its final form, as well a society with different social “layers-strata” or actual roles, virtually settles in a variety of ranges or classification through a theological and legal codification. These virtual schemes or actualizations of shape merge the heterogeneous elements through an interposer agent forming new homogeneous networks and new possibilities.

Therefore, we can say that behind everything and every form is a virtuality or a process of strata and sedimentation forming a final shape through actualization and differentiation. As a personal topic, I would like to delve a little more to the last question posed by De Landa in his essay, “What is a novel or a painting or a piece of music” in this world?, As seen from the point of view of author, I understand the magnitude of the questions and new doubts as arise; Should be art a divergent actualization for society? Is the art and science two heterogeneous elements that should settle into a homogeneous one? Should be the art a real virtuality instead of a virtual reality? How could we reconceptualize the history through art and science?

Author: Gilles Deleuze / Felix Guattari, 1980.

Photo from Faire Rhizome

Deleuze and Guattari introduce the concept of the rhizome as a metaphor for understanding politics, social life, literature, history, and sexuality. A rhizome is “a rootlike subterranean stem, commonly horizontal in position, that usually produces roots below and sends up shoots progressively from the upper surface” (from Dictionary.com, accessed March 16, 2011, based on the Random House Dictionary, Random House 2011). The rhizome “connects any point to any other point” and has “neither beginning nor end, but always a middle from which it grows and which it overspills”. The rhizome morphs, changing in “dimension” and “necessarily… in nature as well.

This is contrasted an “arborial” or tree metaphor which is much more like a hierarchy (roots to trunk to branches to leaves). It is hard to get away from thinking in this more tree-like way, but the rhizome concept forces you to start from the middle, rather than from the bottom or top, and to think in terms of “plateaus” rather than beginnings or endings. The rhizome is made of lines or “lineaments”, but these are not the orderly reporting lines in a “structure” (or hierarchy). As a “plateau is always in the middle, not at the beginning or the end,” a rhizome consists of plateaus. This is a confusing shift of metaphor—to understand this best, do not picture an actual plateau of land but rather the concept of something short of a summit or climax but still other than a beginning or base. The main metaphor is still the rhizome, but the plateau concept essentially means that one is always in the middle, neither at the start nor at some end-stage or goal.
In writing a book as a rhizome, the authors claim that it was written in a non-linear manner; “each plateau can be read starting from anywhere and can be related to any other plateau”. In true interpretive form, the barrier between observer and observed is blurred: “There is no longer a tripartite division between a field of reality (the world) and a field of representation (the book) and a field of subjectivity (the author).” Instead, “an assemblage establishes connections between certain multiplicities drawn from each of these orders”.
Finally, the rhizome is suggested as a model of history, in contrast with a state-centered, hierarchical approach. The state structure reflects “the sedentary point of view”; “What is lacking is a Nomadology, the opposite of history”.

Personal Question:

In this excerpt the authors do not indicate how this rhizome metaphor might be deployed, how an alternative history or “Nomadology” might be written, or what implications the metaphor has more generally. However, it bears a striking similarity to the concept of the network (inspired by the Internet), which has been suggested as an alternative to the hierarchy for organizations. It may be due only to the ingrained metaphor of the pyramid (or the tree, these authors would say) that we find it difficult to imagine other ramifications of the rhizome or network metaphor. What other implications or applications of this metaphor might we identify?